Dictionaries

Dictionaries are used to store data as key-value pairs. They are like a real-world dictionary where we look up a word (the key) to find its definition (the value). Keys must be immutable (strings, integers, tuples), while values can be anything.

Creating and Accessing Dictionaries​

Dictionaries are O(1) fast for lookups and insertions. Since Python 3.7, they keep the order in which we add items.

# Type hinting: specify Key and Value types inside dict[]
# See: [Modern Python Types](../../1 - basics/1.9 - modern-python-types.md) for details
car: dict[str, str | int] = {"brand": "Tesla", "model": "S", "year": 2022}

# Grabbing a value by its key
print(car["brand"])

Output:

Tesla

The .get() Trick​

If we try to access a key that doesn't exist (like car["color"]), Python will crash with a KeyError. Using .get() is safer because it returns None (or a default fallback) instead of crashing.

# Safe way to look up a key
print(car.get("color"))

# We can even provide a default fallback
print(car.get("color", "Not Available"))

None
Not Available

Modifying Dictionaries​

Dictionaries are mutable, so we can add, change, or remove items on the fly.

# Adding or changing items
car["color"] = "Red"
car.update({"year": 2024}) # Updates existing or adds if not found

# Removing items
# pop() removes and returns the value
popped_year = car.pop("year")

print(car)
print(popped_year)

{'brand': 'Tesla', 'model': 'S', 'color': 'Red'}
2024

Merging Dictionaries (Python 3.9+)​

Instead of using update(), which changes the original dictionary, we can use the | (merge) operator to create a brand-new one. The right-side value wins if there's a collision (the second dictionary's value overrides the first).

A = {"x": 1, "y": 2}
B = {"y": 3, "z": 4}

print(A | B)

{'x': 1, 'y': 3, 'z': 4}

Worth Mentioning: Initialization and Bulk Creation​

• setdefault(): Returns the value of a key if it exists; if not, inserts the key with a specified value. Great for initializing nested structures.
• fromkeys(): Creates a new dictionary with keys from a collection and a single value for all.
• clear(): Removes all items from the dictionary.

# setdefault: helpful for counters
counts = {"apples": 10}
counts.setdefault("oranges", 0) # Adds oranges with 0
counts.setdefault("apples", 0)  # Does nothing (apples exists)

# fromkeys: bulk creation
users = dict.fromkeys(["alice", "bob", "charlie"], "standard")

print(counts)
print(users)

# Worth noting: .items() returns a view object (dict_items)
# which is an iterable of (key, value) tuples.
print(users.items())

Output:

{'apples': 10, 'oranges': 0}
{'alice': 'standard', 'bob': 'standard', 'charlie': 'standard'}
dict_items([('alice', 'standard'), ('bob', 'standard'), ('charlie', 'standard')])